Quantile forecasts of inflation under model uncertainty

Bayesian model averaging (BMA) methods are regularly used to deal with model uncertainty in regression models. This paper shows how to introduce Bayesian model averaging methods in quantile regressions, and allow for different predictors to affect different quantiles of the dependent variable. I show that quantile regression BMA methods can help reduce uncertainty regarding outcomes of future inflation by providing superior predictive densities compared to mean regression models with and without BMA.

A study on time-varying quantile and its applications

This Thesis is the result of my Master Degree studies at the Graduate School of Economics, Getúlio Vargas Foundation, from January 2004 to August 2006. am indebted to my Thesis Advisor, Professor Luiz Renato Lima, who introduced me to the Econometrics' world. In this Thesis, we study time-varying quantile process and we develop two applications, which are presented here as Part and Part II. Each of these parts was transformed in paper. Both papers were submitted. Part shows that asymmetric persistence induces ARCH effects, but the LMARCH test has power against it. On the other hand, the test for asymmetric dynamics proposed by Koenker and Xiao (2004) has correct size under the presence of ARCH errors. These results suggest that the LM-ARCH and the Koenker-Xiao tests may be used in applied research as complementary tools. In the Part II, we compare four different Value-at-Risk (VaR) methodologies through Monte Cario experiments. Our results indicate that the method based on quantile regression with ARCH effect dominates other methods that require distributional assumption. In particular, we show that the non-robust method ologies have higher probability to predict VaRs with too many violations. We illustrate our findings with an empirical exercise in which we estimate VaR for returns of São Paulo stock exchange index, IBOVESPA, during periods of market turmoil. Our results indicate that the robust method based on quantile regression presents the least number of violations.

Evaluating Value-at-Risk models via Quantile regressions

This paper is concerned with evaluating value at risk estimates. It is well known that using only binary variables to do this sacrifices too much information. However, most of the specification tests (also called backtests) avaliable in the literature, such as Christoffersen (1998) and Engle and Maganelli (2004) are based on such variables. In this paper we propose a new backtest that does not realy solely on binary variable. It is show that the new backtest provides a sufficiant condition to assess the performance of a quantile model whereas the existing ones do not. The proposed methodology allows us to identify periods of an increased risk exposure based on a quantile regression model (Koenker & Xiao, 2002). Our theorical findings are corroborated through a monte Carlo simulation and an empirical exercise with daily S&P500 time series.

The firm size wage premium : a quantile analysis

Empirical evidence shows that larger firms pay higher wages than smaller ones. This wage premium is called the firm size wage effect. The firm size effect on wages may be attributed to many factors, as differentials on productivity, efficiency wage, to prevent union formation, or rent sharing. The present study uses quantile regression to investigate the finn size wage effect. By offering insight into who benefits from the wage premi um, quantile regression helps eliminate and refine possible explanations. Estimated results are consistent with the hypothesis that the higher wages paid by large firms can be explained by the difference in monitoring costs that large firms face. Results also suggest that more highly skilled workers are more often found at larger firms .

Quantile Inferences for Inflation and Its Variability: Does a Threshold Inflation Rate Exist?

Using quantile regressions and cross-sectional data from 152 countries, we examine the relationship between inflation and its variability. We consider two measures of inflation - the mean and median - and three different measures of inflation variability - the standard deviation, coefficient of variation, and median deviation. Using the mean and standard deviation or the median and the median deviation, the results support both the hypothesis that higher inflation creates more inflation variability and that inflation variability raises inflation across quantiles. Moreover, higher quantiles in both cases lead to larger marginal effects of inflation (inflation variability) on inflation variability (inflation). Using the mean and the coefficient of variation, however, the findings largely support no correlation between inflation and its variability. Finally, we also consider whether thresholds for inflation rate or inflation variability exist before finding such positive correlations. We find evidence of thresholds for inflation rates below 3 percent, but mixed results for thresholds for inflation variability.

Determinantes do consumo de frutas e hortaliças em adolescentes por regressão quantílica

OBJETIVO: Analisar o consumo de frutas, legumes e verduras (FLV) de adolescentes e identificar fatores associados. MÉTODOS: Estudo transversal de base populacional com amostra representativa de 812 adolescentes de ambos os sexos de São Paulo, SP, em 2003. O consumo alimentar foi medido pelo recordatório alimentar de 24 horas. O consumo de FLV foi descrito em percentis e para investigar a associação entre a ingestão de FLV e variáveis explanatórias; foram utilizados modelos de regressão quantílica. RESULTADOS: Dos adolescentes entrevistados, 6,4% consumiram a recomendação mínima de 400 g/dia de FLV e 22% não consumiram nenhum tipo de FLV. Nos modelos de regressão quantílica, ajustados pelo consumo energético, faixa etária e sexo, a renda domiciliar per capita e a escolaridade do chefe de família associaram-se positivamente ao consumo de FLV, enquanto o hábito de fumar associou-se negativamente. Renda associou-se significativamente aos menores percentis de ingestão (p20 ao p55); tabagismo aos percentis intermediários (p45 ao p75) e escolaridade do chefe de família aos percentis finais de consumo de FLV (p70 ao p95). CONCLUSÕES: O consumo de FLV por adolescentes paulistanos mostrou-se abaixo das recomendações do Ministério da Saúde e é influenciado pela renda domiciliar per capita, pela escolaridade do chefe de família e pelo hábito de fumar.

Bond fund runs: The financial crisis case

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Credit default swap (CDS) prediction model & trading strategy

This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

The Determinants of Entry are not Independent of Start-up Size: Some evidence from Spanish manufacturing

In this paper we explore the determinants of firm start-up size of Spanish manufacturing industries. The industries' barriers to entry affect the ability of potential entrants to enter the markets and the size range at which they decide to enter. In order to examine the relationships between barriers to entry and size we applied the quantile regression techniques. Our results indicate that the variables that characterize the structure of the market, the variables that are related to the behaviour of the incumbent firms and the rate of growth of the industries generate different barriers depending on the initial size of the entrants. Keywords: Entry, regression quantiles, start-up size. JEL classification: L110, L600

Analyzing aggregate real exchange rate persistence through the lens of sectoral data

In this paper we analyze the persistence of aggregate real exchange rates (RERs) for a group of EU-15 countries by using sectoral data. The tight relation between aggregate and sectoral persistence recently investigated by Mayoral (2008) allows us to decompose aggregate RER persistence into the persistence of its different subcomponents. We show that the distribution of sectoral persistence is highly heterogeneous and very skewed to the right, and that a limited number of sectors are responsible for the high levels of persistence observed at the aggregate level. We use quantile regression to investigate whether the traditional theories proposed to account for the slow reversion to parity (lack of arbitrage due to nontradibilities or imperfect competition and price stickiness) are able to explain the behavior of the upper quantiles of sectoral persistence. We conclude that pricing to market in the intermediate goods sector together with price stickiness have more explanatory power than variables related to the tradability of the goods or their inputs.

Heterogeneity across immigrants in the Spanish labour

The purpose of this paper is to analyze the diferences that immigrants have in the Spanish labour market. Immigrants in Spain come from a diversity of continents (Africa, South America, Eastern Europe, Asia, etc.), and there are substantial diferences in characteristics not only among continents but also among countries in each continent. Using a quantile regression method of decomposition we estimate these diferences that are reflected in the labour market and in particular are mirrored in the wage, so some immigrants are more discriminated or segregated that others because they have less advantage. For example Argentineans and Peruvians have the same origin and culture but we can find diferences in the wage that they receive in the Spanish labor market, or for example Moroccans have a advantage with respect to the Rest of Africans, due to the geographical proximity to Spain. So when we study the pay gap and the gender pay gap we need to take into consideration the origin of immigrants. We also want to study how the integration of immigrants evolved across years, whether the wage gap that we find in the first episode of work between immigrants and natives disappears or continues to be present in the Spain labour market.

Innovation and absorptive capacity: What is the role of technological frontier?

This paper explores how absorptive capacity affects the innovative performance and productivity dynamics of Spanish firms. A firm’s efficiency levels are measured using two variables: the labour productivity and the Total Factor Productivity (TFP). The theoretical framework is based on the seminal contributions of Cohen and Levinthal (1989, 1990) regarding absorptive capacity; and the applied framework is based on the four-stage structural model proposed by Crépon, Duguet and Mairesse (1998) for setting the determinants of R&D, the effects of R&D activities on innovation outputs, and the impacts of innovation on firm productivity. The present study uses a twostage structural model. In the first stage, a probit estimation is used to investigate how the sources of R&D, the absorptive capacity and a vector of the firm’s individual features influence the firm’s likelihood of developing innovations in products or processes. In the second phase, a quantile regression is used to analyze the effect of R&D sources, absorptive capacity and firm characteristics on productivity. This method shows the elasticity of each exogenous variable on productivity according to the firms’ levels of efficiency, and thus allows us to distinguish between firms that are close to the technological frontier and those that are further away from it. We used extensive firm-level panel data from 5,575 firms for the 2004-2009 period. The results show that the internal absorptive capacity has a strong impact on the productivity of firms, whereas the role of external absorptive capacity differs according to nature of the each industry and according the distance of firms from the technological frontier. Key words: R&D sources, innovation strategies, absorptive capacity, technological distance, quantile regression.

High Growth Firms and Innovation: an empirical analysis for Spanish firms

This paper analyzes the effect of firms’ innovation activities on their growth performance. In particular, we observe how important innovation is for high-growth firms (HGFs) for an extensive sample of Spanish manufacturing and services firms. The panel data used comprises diverse waves of Spanish CIS over the the period 2004-2008. First, a probit analysis determines whether innovation affects the probability of being a high-growth firm. And second, a quantile regression technique is applied to explore the determinants and characteristics of specific groups of firms (manufacturing versus service firms and high-tech versus low-tech firms). It is revealed that R&D plays a significant role in the probability of becoming a HGF. Investment in internal and external R&D per employee has a positive impact on firm growth (although internal R&D presents a significant impact in the last quantiles, external R&D is significant up to the median). Furthermore, we show evidence that there is a positive impact of employment (sales) growth on the sales (employment) growth. Keywords: high-growth firms, firm growth, innovation activity JEL Classifications: L11, L25, O30

Changes in wage structure in Mexico going beyond the mean: An analysis of differences in distribution, 1987-2008

This paper conducts an empirical analysis of the relationship between wage inequality, employment structure, and returns to education in urban areas of Mexico during the past two decades (1987-2008). Applying Melly’s (2005) quantile regression based decomposition, we find that changes in wage inequality have been driven mainly by variations in educational wage premia. Additionally, we find that changes in employment structure, including occupation and firm size, have played a vital role. This evidence seems to suggest that the changes in wage inequality in urban Mexico cannot be interpreted in terms of a skill-biased change, but rather they are the result of an increasing demand for skills during that period.

Catastrophic medical expenditure risk

Medical expenditure risk can pose a major threat to living standards. We derive decomposable measures of catastrophic medical expenditure risk from reference-dependent utility with loss aversion. We propose a quantile regression based method of estimating risk exposure from cross-section data containing information on the means of financing health payments. We estimate medical expenditure risk in seven Asian countries and find it is highest in Laos and China, and is lowest in Malaysia. Exposure to risk is generally higher for households that have less recourse to self-insurance, lower incomes, wealth and education, and suffer from chronic illness.